Virtually every visual and visuomotor function hinges first and foremost on the visual system's ability to consistently and accurately localize stimuli, and this is especially true in cluttered and dynamic scenes. However, it is unknown what sorts of information are integrated to determine perceived position, how such integration occurs, or what the neural mechanism(s) and loci of this process are. Perceptual localization in typically cluttered and dynamic scenes requires the visual system to both assign and update object positions; to do this it relies not just on the retinal location of the object of interest, but als principally on four additional factors: visual motion, frames of reference, eccentricity biases, an contrast adaptation. To understand how the visual system assigns and updates object positions, we must approach the task of localization not as an isolated process, but as an integrative one-one that depends on contextual information in the scene. Our proposed experiments have two goals; first, to psychophysically measure perceived position as a function of retinal position, contrast adaptation, visual motion, eccentricity bias, and frames of reference in order to generate a novel multifactorial integration field model; we will use this model in fMRI experiments to test the hypothesis that neurotopic organization across visual cortex is heterogeneous (unique position codes in each visual area) or homogeneous (identical across visual areas). Our pilot results suggest that there are unique position codes in different visual areas. The second goal of the proposal is to test whether these unique position codes (the differences in topographic organization) have perceptual consequences. We will use psychophysics to test these predicted double dissociations in perceived location and then use TMS to test the causal contribution of heterogeneous visual cortical topographic organization to perceived position. One novelty of our approach lies in developing a new mixed generative and discriminative model of spatial coding, that can be applied to psychophysical and fMRI data in tandem, and further allows us to make predictions from fMRI results about perceptual outcomes in specific situations. The causal relationship between fMRI results and perceptual outcomes will then be tested with TMS. Our experiments will provide novel insight on how cues are integrated to determine perceived position at each stage of visual processing, which is crucial to understanding the fundamental localization deficits that occur in a range of visual and cognitive impairments ranging from amblyopia and macular degeneration, to autism. Until we understand how position is assigned in the typical brain, we lack the necessary insight to develop diagnostic tools, predictive markers, and treatment outcome measures for these impairments.